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Applied Sciences
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Planning and Operation of Low Voltage Distribution System
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Planning and Operation of Low Voltage Distribution System

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (25 June 2023) | Viewed by 5387

Special Issue Editor

Dr. Gian Giuseppe Soma

E-Mail Website
Guest Editor
Department of Electrical and Electronic Engineering, University of Cagliari, via Marengo 2, 09123 Cagliari, Italy
Interests: distribution network planning; microgrids; distributed generation; optimization; distribution network optimization; electric vehicles; active distribution networks; ancillary services markets
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are inviting submissions to a Special Issue of Applied Sciences on the subject of "Planning and Operation of Low Voltage Distribution System".

Electric distribution systems have been central to recent efforts in the modernization and decarbonization of electric grids. There are unprecedented challenges in the modeling and analysis of distribution grids due to large-scale integration of advanced equipment including smart grid assets and inverter-based distributed energy resources (IBDERs). To assess the potential impacts of increasing IDBERs and advanced distribution system equipment in a more comprehensive manner, there is a need for the establishment of highly accurate and efficient simulation softwares. Simulation tools depend on component models and numerical analysis techniques.

In the future, power distribution companies will need to plan, operate, and innovate in a variety of new ways to respond to changing power system resources and opportunities, especially in the low voltage distribution networks. In fact, in those type of network suitable and innovative methodologies for the planning and operation are not available in the state of the art. The use of renewable energy sources is moving generation from the top to the bottom of power systems, where, traditionally, only loads existed. Active demand, distribution energy storage devices, and electric vehicles are going to drastically change the way distribution systems will be operated. In opposition to conventional approaches, modern distribution planning algorithms should emulate the new environment to produce expansion and strategic plans for guiding the evolution of system in times of financial austerity.

In this Special Issue, we invite original submissions of new research outcomes that highlight innovations in the areas of Planning and Operation of Low Voltage Electric Distribution System.

Topics of interests include but are not limited to the following:

  • Innovative planning techniques of low voltage distribution networks;
  • Probabilistic approach in low voltage distribution network planning;
  • Multi-Objective approach in low voltage distribution network planning;
  • Smart management of DER in low voltage distribution networks;
  • Impact of the Electric Vehicles in low voltage distribution network planning;
  • Low voltage distribution networks with microgrids/nanogrids architectures

Dr. Gian Giuseppe Soma
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

15 pages, 2898 KiB  
Article
Relationship between Fault Level and System Strength in Future Renewable-Rich Power Grids
by Rafat Aljarrah, Mazaher Karimi, Hesamoddin Marzooghi, Sahban Alnaser, Murad Al-Omary, Qusay Salem and Salman Harasis
Appl. Sci. 2023, 13(1), 142; https://doi.org/10.3390/app13010142 - 22 Dec 2022
Cited by 2 | Viewed by 3278
Abstract
The fault level is used as a simple indicator for scanning the system strength in power systems. To an extent, this has proven its efficacy in classical power systems based on synchronous generation (SG). However, power electronics-based renewable energy sources (RESs), due to [...] Read more.
The fault level is used as a simple indicator for scanning the system strength in power systems. To an extent, this has proven its efficacy in classical power systems based on synchronous generation (SG). However, power electronics-based renewable energy sources (RESs), due to their controlled and limited fault current contribution, may affect the impedance, fault level, and system strength in a non-linear manner. Hence, this raises a question about the validity of using the fault level as a measure reflecting the system strength in future grids. This paper intends to shed light on the above question by examining the correlation between the fault level and the system strength in future grid scenarios. This is achieved in two steps: first, by employing the measure-based Thevenin impedance for fault level estimation in renewable-rich grids, and second, by comparing these estimated fault levels with those obtained from steady-state and dynamic simulations. While the results have demonstrated the suitability of using the fault level for system strength scanning in scenarios of low penetration of RESs, they revealed that such a tool might be misleading with very high RES penetrations. The findings have been verified using the adjusted IEEE nine-bus test system in DIgSILENT PowerFactory. Full article
(This article belongs to the Special Issue Planning and Operation of Low Voltage Distribution System)
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28 pages, 4431 KiB  
Article
A Machine-Learning Pipeline for Large-Scale Power-Quality Forecasting in the Mexican Distribution Grid
by Juan J. Flores, Jose L. Garcia-Nava, Jose R. Cedeno Gonzalez, Victor M. Tellez, Felix Calderon and Arturo Medrano
Appl. Sci. 2022, 12(17), 8423; https://doi.org/10.3390/app12178423 - 24 Aug 2022
Cited by 5 | Viewed by 1398
Abstract
Electric power distribution networks face increasing factors for power-quality (PQ) deterioration, such as distributed, renewable-energy generation units and countless high-end electronic devices loaded as controllers or in standalone mode. Consequently, government regulations are issued worldwide to set up strict PQ distribution standards; the [...] Read more.
Electric power distribution networks face increasing factors for power-quality (PQ) deterioration, such as distributed, renewable-energy generation units and countless high-end electronic devices loaded as controllers or in standalone mode. Consequently, government regulations are issued worldwide to set up strict PQ distribution standards; the distribution grids must comply with those regulations. This situation drives research towards PQ forecasting as a crucial part of early-warning systems. However, most of the approaches in the literature disregard the big-data nature of the problem by working on small datasets. These datasets come from short-scale off-grid configurations or selected portions of a larger power grid. This article addresses a study case from a region-sized state-owned Mexican distribution grid, where the company must preserve essential PQ standards in approximately 700 distribution circuits and 150 quality-control nodes. We implemented a machine-learning pipeline with nearly 4000 univariate forecasting models to address this challenge. The system executes a weekly forecasting pipeline and daily data ingestion and preprocessing pipeline, processing massive amounts of data ingested. The implemented system, MIRD (an acronym for Monitoreo Inteligente de Redes de Distribution—Intelligent Monitoring of Distribution Networks), is an unprecedented effort in the production, deployment, and continuous use of forecasting models for PQ indices monitoring. To the extent of the authors’ best knowledge, there is no similar work of this type in any other Latin-American distribution grid. Full article
(This article belongs to the Special Issue Planning and Operation of Low Voltage Distribution System)
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